Multiclass feature selection with metaheuristic optimization algorithms: a review
Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …
selection is harder to perform since most classifications are binary. The feature selection …
The monarch butterfly optimization algorithm for solving feature selection problems
M Alweshah, SA Khalaileh, BB Gupta… - Neural Computing and …, 2022 - Springer
Feature selection (FS) is considered to be a hard optimization problem in data mining and
some artificial intelligence fields. It is a process where rather than studying all of the features …
some artificial intelligence fields. It is a process where rather than studying all of the features …
Opposition-based sine cosine optimizer utilizing refraction learning and variable neighborhood search for feature selection
This paper proposes new improved binary versions of the Sine Cosine Algorithm (SCA) for
the Feature Selection (FS) problem. FS is an essential machine learning and data mining …
the Feature Selection (FS) problem. FS is an essential machine learning and data mining …
An immune genetic algorithm for solving NPV-based resource constrained project scheduling problem
The net present value (NPV)-based resource constrained project scheduling problem
(RCPSP) is a well-known scheduling problem in many industries, such as construction …
(RCPSP) is a well-known scheduling problem in many industries, such as construction …
[HTML][HTML] Fractional order adaptive hunter-prey optimizer for feature selection
Proposing a reliable feature selection approach is the primary stone for endorsing the
prediction performance; therefore, this paper proposes an enhanced optimization technique …
prediction performance; therefore, this paper proposes an enhanced optimization technique …
Integration of ensemble and evolutionary machine learning algorithms for monitoring diver behavior using physiological signals
A Koohestani, M Abdar, A Khosravi, S Nahavandi… - IEEE …, 2019 - ieeexplore.ieee.org
The level of consciousness and the concentration of drivers while driving play a vital role for
reducing the number of accidents. In recent decade, in-vehicle infotainment (IVI)[or in-car …
reducing the number of accidents. In recent decade, in-vehicle infotainment (IVI)[or in-car …
Multi-core sine cosine optimization: Methods and inclusive analysis
Abstract The Sine Cosine Algorithm (SCA) is a popular population-based optimization
method, which has shown competitive results compared to other algorithms, and it has been …
method, which has shown competitive results compared to other algorithms, and it has been …
Internet of things sensor assisted security and quality analysis for health care data sets using artificial intelligent based heuristic health management system
M Amoon, T Altameem, A Altameem - Measurement, 2020 - Elsevier
The developments in the medical systems, especially in health care management systems,
play a vital role in patients. The effective management of health records leads to an increase …
play a vital role in patients. The effective management of health records leads to an increase …
Enhanced fault diagnosis of wind energy conversion systems using ensemble learning based on sine cosine algorithm
K Attouri, K Dhibi, M Mansouri, M Hajji… - Journal of Engineering …, 2023 - Springer
This paper investigates the problem of incipient fault detection and diagnosis (FDD) in wind
energy conversion systems (WECS) using an innovative and effective approach called the …
energy conversion systems (WECS) using an innovative and effective approach called the …
[HTML][HTML] State-of-the-art methods in healthcare text classification system: AI paradigm
Machine learning has shown its importance in delivering healthcare solutions and
revolutionizing the future of filtering huge amountd of textual content. The machine …
revolutionizing the future of filtering huge amountd of textual content. The machine …